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Algebraic Laws for Nondeterminism and Concurrency

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Algebraic Laws for Nondeterminism and Concurrency Algebraic Laws for Nondeterminism and Concurrency MATTHEW HENNESSY AND ROBIN MILNER University of Edinburgh, Edinburgh, Scotland Abstract. Since a nondeterministic and concurrent program may, in general, communicate repeatedly with its environment, its meaning cannot be presented naturally as an input/output function (as is often done in the denotational approach to semantics). In this paper, an alternative is put forth. First, a definition is given of what it is for two programs or program parts to be equivalent for all observers; then two program parts are said to be observation congruent iff they are, in all program contexts, equivalent. The behavior of a program part, that is, its meaning, is defined to be its observation congruence class. The paper demonstrates, for a sequence of simple languages expressing finite (terminating) behaviors, that in each case observation congruence can be axiomatized algebraically. Moreover, with the addition of recursion and another simple extension, the algebraic language described here becomes a calculus for writing and specifying concurrent programs and for proving their properties. Categories and Subject Descriptors: F.3.2 [Logics and Meanings of Programs]:Semantics of Program- ming Languages-algebraic approaches to semantics General Terms: Theory Additional Key Words and Phrases: Communicating processes,observational equivalence 1. Introduction The denotational approach to the semantics of programming languageshas been well developed in recent years [ 1, 111and applied successfullyto many nontrivial languages.Even languageswith parallel constructs have been treated in this way, using the power-domain constructions of [3], [7], and [lo]. Indeed for such languagesthere is no shortage of possible denotational models. For example, there are severalsimple variations on the model for processes,introduced in [4]. In the face of such an abundance, it is best to recall the motivation for seeking such models. They provide a useful mathematical framework for the analysis of programs, and for developing logical systemsfor proving their properties. However, if either the mathematics or the logic is to have any relevance,a link must be made between the denotational model and the behavior, or operational semantics,of the programs. One way of making the link is to demand that the denotational model befully abstract with respectto the operational semantics.This means simply that two program phrases should have the same denotation if, and only if, the opera- A preliminary version of this paper, entitled “On Observing Nondeterminism and Concurrency,” appeared in the Proceedings of the 7th Colloquium on Automata, Languages and Programming. Lecture Notes in Computer Science, vol. 85. Springer-Verlag, New York, Berlin, Heidelberg, 1980, pp. 299- 309. Those. portions that appeared in the preliminary are reprinted with permission of Springer-Verlag. Authors’ address: Department of Computer Science, James Clerk Maxwell Building, The Kings Buildings, University of Edinburgh, Mayfield Road, Edinburgh EH9 352, Scotland. Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the ACM copyright notice and the title of the publication and its date appear, and notice is given that copying is by permission of the Association for Computing Machinery. To copy otherwise, or to republish, requires a fee and/or specific permission. 0 1985 ACM 0004-541 l/85/0100-0137 $00.75 Journal of the Association for Computing Machinery. Vol. 32, No. I, January 1985, pp. 137-161 138 M. HENNESSYAND R. MILNER tional meaning of every program remains unchanged when one phrase is replaced by the other. What exactly is meant by the behavior of nondeterministic or concurrent programs is far from clear and in this paper we put forth one possible definition. The essenceof our approach is that the behavior of a program is determined by how it communicates with an observer.We begin by assumingthat every program action is observable in this way; later we allow that some actions (in particular, internal communications between concurrent components) are not observable. We apply our d.efinition to a sequence of simple languages for expressing programs with finite behavior, and show that in each case it can be characterized by algebraic axioms. This leads automatically to a fully abstract model; it is just the initial algebra generated by the axioms. Moreover, a proper understanding of the finite case seerns a necessary prelude to a study of programs with infinite behavior. Such programs may be gained simply by adding recursion to our languages. In fact, with the alddition of recursion and with a natural extension to allow data valuesto be communicated between concurrently active agents,the simple algebra described here becomesa languagefor writing and specifying concurrent programs and for proving their properties. This languagewas introduced in [5]; it was partly the need for a firm basis for the algebraic laws discussed there that led to the present study of observation equivalence. In Section 2 we present our general framework. In Sections 3-6 we outline and summarize our results for the languagesconsidered. Proofs of the main results are contained in Appendixes A-C. The present paper is a full presentation, complete with proofs, of results first announced without proof in [2]. 2. Observational Equivalence of Processes 2.1. EQUIVALENCE. In this section we introduce a way of defining equivalence between programs t.hat is based entirely on operational considerations; informally, two programs are equivalent when no observations can distinguish them. Further, two subprograms or program phrasesare congruent if the result of placing each of them in any progralm context yields two equivalent programs. Then, considering the phrasesas modules, one can be exchangedfor the other in any program without affecting the observedbehavior of the latter. However, much is left vague by this prescription. First, what are obse;ations? Second, how can they be used to distinguish programs? In this section we answer these two questions, thereby obtaining a precise notion of equivalence, and hence also of congruence. Note that the answer to the first question does not determine the answer to the second; observations may be used in many different ways to distinguish more or fewer programs. We cannot argue that our answer is best, only that it is natural; to this end, we give an alternative characterization of the resulting equivalence relation in Section 2.2. In the caseof deterministic sequential programs, the behavior of a program p is usually taken to be its input-output function IO(p). Here, an observation of p is taken to be a pair of states(or values):an input state and the resulting output state (if any). Then proyFamsp and q are equivalent, written p - q, if they yield the same observation sets; that is, if IO(p) = IO(q). The corresponding congruence relation -c is then defined as follows: p -c q if for every suitable program context 55[ 1, JZb] - .Y[q]. If the language is defined algebraically, that is, by operations Algebraic Laws for Nondeterminism and Concurrency 139 for constructing new programs from ones already defined, the wCturns out to be the largest congruence relation included in -. However, any satisfactory comparison of the behavior of concurrent programs must take into account their intermediate states as they progress through a computation, because differing intermediate states can be exploited in different program contexts to produce different overall behavior (e.g., deadlock). With this in mind, we now proceed to a more refined notion of behavioral equivalence, which we call observational equivalence. This notion may be defined for objects more general than programs, which (for the remainder of the present section) we shall call processes. Let P, then, be a set of objects that we may think of as processes.We take the view that any observation of p E P entails some participation by p itself; p is an active participant, as well as the observer. Thus, the act of observing a process changesits state. So if we adopt the familiar technique of identifying the state of a processwith the processitself, we can say that observation changesthe processinto a new process.This changemay not be deterministic; hence the effect of a particular type of observation-applied to an arbitrary process-may be captured by a binary relation over P. In general, we presupposea set Z of possible types of observation, so we then have a set (Ri C P x P, i E I) of observation relations. Using these relations, we define a sequence of equivalence relations -” over P (n 2 0), in such a way that N~+IC -,,, as follows: p m. q ifp, q E P (i.e., m. = P x P); p -n+l q if for every i E Z, (i) (p, p’) E Ri implies, for some q’, (q, q’) E R; and p’ -,, q’; (ii) (q, q’ ) E Ri implies, for some p’, (p, p’) E Ri and p’ -R q’. Then p and q are observationally equivalent, written p - q, if p -,, q for every n. Thus, we have defined - to be fl, -,,. In fact, we have taken - to be the limit n, E”( P x P), where E(S) is defined for any S G P x P as follows: (p, q) E E(S) if for every i E Z (i) (p, p’) E Ri implies, for some q’, (q, q’) E Ri and (p’, q’) E S; (ii) (q, q’ ) E Ri implies, for some p’, (p, p’) E Ri and (p’, q’) E S. Now if E has the property that E(fl, Sn) = fl, (E(S,)) for every decreasing sequenceS, of relations, that is if E is anticontinuous, then it follows from classical fixed-point theory that - is the maximum fixed-point of the map E of relations. Let us say that R C P x P is image-finite if, for each p E P, (p’ 1(p, p’) E RJ is finite.
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